Unique identifiers

MOST studies will typically have a longitudinal component with individual participants returning, in person and/or online, for multiple activities. Consideration should be given to how individuals will be recognized over time.

Assessments

MOST studies will typically have at least four kinds of assessments of individual participants:

1. screening for eligibility
2. locator information to facilitate contact with individuals over time
3. baseline interview
4. one or more follow-up interviews

It is important to keep in mind that some individuals who are screened will not be eligible, and therefore will not continue into the main study. There also may be a lag of uncertain length between the start of screening for a potential participant and enrollment of that participant if eligible. For REDCap setup, the implication is that screening should be a separate piece of the study. This allows the timing of follow-up interviews and intervention activities to depend on the date of enrollment/baseline rather than the date on which screening started.

Locator information with ongoing updates

A number of REDCap fields will be devoted to information to facilitate contacting individual participants over time for study activities. These may include:

1. cell phone number
2. email address
3. mailing address
4. names and contact information for family members, friends, or service programs likely to know where/how to find an individual participant

These fields may be entered and updated by project staff rather than participants directly. REDCap allows different users (i.e., staff on the project) to have or not have the rights to do different things within the system, and locator may be one part of the project where access is limited to specific staff.

Locator information can be updated when an individual participant is present for an assessment or intervention activity, so think about how updates to locator fields will be integrated into a regular project workflow.

Intervention component activities

Think of fields needed within REDCap to document aspects of intervention component delivery. Components may be sessions with individual participants, group activities, or technology (e.g., text messages). At a minimum, the date, staff, duration, and completion status of an activity should be captured. Other fields related to intervention activities may include ratings of fidelity, measures of engagement/satisfaction, and descriptions of content discussed.

Condition-specific activities and data collection

The typical MOST study will have at least four different conditions and may have many more conditions. Some study activities and data collection will be condition-specific (only relevant for some of the study conditions). As will be described below, REDCap has a way to define events and related data collection that are specific to subsets of study participants.

Need to monitor and drive completion of common and condition-specific study activities

REDCap divides the whole study into arms, which are groups of events which may be common to all participants or specific to a subset of participants.

To be more concrete, a participant in a condition which is assigned to the active level of a component gets events specific to that component (e.g., an intervention session). Other events, such as a baseline interview, will be common to many more participants. Some events may be univeral, such as a screening interview to determine eligibility for the study. Event scheduling and data collection within the REDCap system is on an as needed basis.

Keeping track of intervention components and study conditions

As you prepare to set up REDCap to manage a study, it can be useful to create a table showing the study conditions and which level of each component they receive. Giving the study conditions names, rather than referring to them only with numbers or letters, can make it easier for staff to think about and discuss to activities needed for specific conditions. Consider a 2 x 2 x 2 full factorial design. A table to guide REDCap setup may look something like this:

In this example, study conditions are given fish names. With more than 16 conditions, names may not be helpful/feasible. Each study condition will have a unique set of planned activities, which REDCap calls events. Part of setting up a REDCap project for the study will involve mapping out all of the events each condition will experience, and at each of these events, one or more instruments may be designated for data collection.

Ways to build a REDCap project

In addition to the various whole project settings within REDCap, there are two ways to build the data collection fields of a REDCap project: the online designer and the data dictionary.

Online Designer

The online designer is an intuitive, point-and-click interface which allows users to build data collection fields. Online designer also allows users to select instruments from the REDCap Shared Library, a repository of instruments which can be selected and inserted into your own project. If an instrument the project needs exists within the library, this can save time and reduce errors.

Figure 3. Online Designer

This is what the interface to add a new field within online designer looks like:

Figure 4. Add Fields with Online Designer

Data Dictionary

The data dictionary is a comma-delimited file with a very specific structure that can be used to specify fields in REDCap. An advantage of working directly in the data dictionary is that similar items can be setup more quickly by copying and pasting aspects of fields that are shared across the items. Many of the cells in the data dictionary may be blank/unused.

Figure 5. Data Dictionary

Here is a brief description of the content specified in each of the 18 columns of the data dictionary:

Column	Description
1. Variable / Field Name	A short name for the field which will become a variable name in exported data
2. Form Name	Identifies a group of fields that go together; for example, locator form groups locator fields
3. Section Header	Provides a way to include headers and instructions between data collection elements
4. Field Type	Common types include text, descriptive, radio, checkbox, file, and notes
5. Field Label	More detailed text associated with the field; for example, the content of an interview item
6. Choices, Calculations, OR Slider Labels	Response options or a calculation based on fields collected earlier
7. Field Note	A way to add instructions or other content to the field; for example, “minutes” for a duration
8. Text Validation Type OR Show Slider Number	Specifies the kind/format of data expected; for exampe, date_mdy for a date field
9. Text Validation Min	Minimum allowed value for a field with validation
10. Text Validation Max	Maximum allowed value for a field with validation
11. Identifier?	Flags fields with identifying information (e.g., name) to facilitate deindentified exports
12. Branching Logic (Show field only if…)	A way to specify who should complete the field, based on data collected in other fields
13. Required Field?	Does the field have to be completed before continuing?
14. Custom Alignment	A way to control the alignment of the content shown when the field is completed
15. Question Number (surveys only)	Auto-numbering is available, but custom item numbering for surveys can be specified here
16. Matrix Group Name	A way of grouping fields together into a matrix; fields with the same matrix name go together
17. Matrix Ranking?	Used to rank choices in a matrix group; implies no two fields can have the same value
18. Field Annotation	Not displayed; can be used to set defaults, hide fields, and for other purposes

Both the online designer and the data dictionary allow customization of formatting, as both understand HTML code. The example MOST project illustrates some of these possibilities below.

Interview Items and Other Data Collection Fields

Item types

REDCap offers a wide variety of survey and interview item types.

• Text box (short text, number, date/time, etc)
• Notes box (paragraph text)
• Calculated field (derived from other fields)
• Multiple choice (drop-down list OR radio buttons)
• Checkboxes (check all that apply)
• Yes/No
• True/False
• Signature (with mouse, finger, or other device)
• Slider/Visual Analog
• File upload
• Descriptive text

Figure 6. Field Types

Forms vs. Surveys for Data Collection

Two ways of collecting/entering data in REDCap are Forms and Surveys. Forms are for data entered by project staff, not directly by participants. Forms might be used to enter the results of biological testing or responses to items in a staff-administered personal interview. Surveys are for data entered directly by participants. Surveys may take place at a study field site, as an audio computer-assisted self-interview, or participants could be invited by email (or in other ways) to complete a survey in a location of their choice and with some flexibility around exactly when it happens (e.g., a participant could take a survey by following a link on their home computer at 9:45pm on a Sunday).

Events and Arms

The entry point for setting up events within REDCap is the Project Setup tab. This is where one can define study events and designate instruments used for each event.

Figure 6. Defining Events

Each arm in the project is a collection of events in a sequence. In a MOST study, each condition may have a unique sequence of study events, and arms in REDCap are a way to specify different events for different participants. For study conditions which receive multiple components, REDCap setup is an opportunity to consider the order in which those components will be delivered to participants, and whether temporal overlap among components is permissible or not. REDCap setup is a good time to consider how intervention component activities and assessment activities are temporally organized.

Think about the timeline of study events for an invidual study participant. All potential participants start with screening events used to determine eligibility. This is a one of the events which will be common to all participants. Other events common to all participants may be: 1) a baseline interview; 2) randomization to a condition; and 3) one or more follow-up interviews. Based on the results of randomization, condition-specific events will come into play. The typical MOST study will need at least one arm for the common events occuring prior to randomization as well as arms for each unique study condition. For example, a 2 * 2 * 2 full factorial design with 8 unique conditions would have at least nine arms in REDCap.

Scheduling and Calendar Application

Repeating Events and Instruments

REDCap has the ability to repeat a data collection instrument or an entire event of instruments an unlimited number of times without having to specify the amount needed. This is sometimes called one-to-many data collection, in which a project can have one or more repeating parts. For example, if each record in a hypothetical project represents a person, then one might have a repeating instrument for medications, one for family members, one or adverse events, and one for collecting data over multiple visits (or weekly surveys), so that each repeating element is connected to the overall record but can repeat independently of the other instruments. So if using repeating instruments or repeating events, each record in the project can have a different number of repeated instances of any given instrument or event. One record may have five medications, but another may have two or none, for example. Such flexibility makes this feature very powerful, and setting up repeating instruments and/or repeating events in a project is very quick and easy. The repeating instruments/events feature can be enabled and set up by clicking the Enable button in the Optional Modules section on the Project Setup page.

Randomization Module

The randomization module sets up REDCap to randomly assign participants to specific study groups.
Setup includes the following steps:
1. Define your randomization model
2. Download template allocation tables (as Excel/CSV files)
3. Upload your allocation table (CSV file)

Randomization can be stratified by one or more variables collected before the randomization step. User rights functionality can control which project staff are allowed to randomize. After the value of the random group is assigned, the random group field becomes read-only and the value can not be changed (by design!).

The table of allocations used by REDCap is generated outside of REDCap and saved in comma-delimited format. The comma-delimited allocation table is uploaded to REDCap as the third and final step in setting up the randomization module. In the example shown in the figure below, participants are assigned to one of eight study conditions and random assignment is stratified by gender.

Include more assignments than you believe you will need in the table of allocations to allow for participant drop-out and drop-in as well as uncertainty in the proportion of participants enrolled in each strata. For example, if the study design calls for randomization to eight conditions stratified by gender and forty participants in each condition, you might generate an allocation table with sixty assignments per condition in each strata (i.e., a total of 60 * 8 * 2 = 960).

Here is an example of generating the allocation table for stratified random assignment using R:

library(tidyverse)
DF <- expand.grid(Person = 1:800, gender = 1:2)
DF <- DF %>% mutate(Block = cut(Person, 100))
set.seed(732212)
DF <- DF %>% 
  group_by(gender, Block) %>% 
  mutate(scond = sample(1:8)) %>% 
  ungroup()
write.table(DF %>% select(scond, gender), file = "atab.csv", row.names = FALSE, sep = ",")

Randomization Dashboard

When the project is underway and some participants have been assigned to conditions, the Randomization Module includes a dashboard showing the number of participants (records) assigned to each condition in each strata, which is useful for tracking enrollment progress.

Figure 8. Randomization Module Dashboard

Reports

Reports can show data fields to understand collected data and facilitate project management.
There are four steps to building a report:
1. Select users who can access the report
2. Select data fields to include in the report
3. Select cases to include using logic applied to data fields (e.g., only show female participants)
4. Select data fields used to order the results (e.g., sort report by age)

Figure 9. Reports Example

Record Status Dashboard

The Record Status Dashboard allows project staff to see which data entry forms have been completed for different individual participants.

Figure 10. Record Status Dashboard

Data Export

Data from smaller projects can be exported manually within REDCap too

REDCap can export to the following formats: comma-delimited; SPSS; SAS; R; Stata; and XML. The export interface can be accessed from the Project Home tab of your REDCap project.

Figure 11. Manual Data Export within REDCap

Things more easily done outside of REDCap

It is very likely you will want and need to do things with the collected data that are impossible or difficult to do within the REDCap system. A fairly efficient approach is to regularly export data from REDCap, and then generate the summaries and files needed to facilitate project management. The ability to use an application programming interface (API) to pull data from REDCap in a program greatly improves the efficiency of this workflow. I have used a combination of tools including various R packages and GitHub to support the Heart-to-Heart 2 MOST study. The redcapAPI R package uses the REDCap API to pull current project data, then there are many data management, summarizing, and list making steps in R, and web pages generated in R are hosted on GitHub. GitHub and similar tools have options for both public and private repositories. In addition to the web pages, it can be useful to generate MS-Excel files which list individual participants and highlight completed and needed study activities. The openxlsx R package can be used to write MS-Excel files from R.

Review intervention activity gaps

Generating a simple list of participants with intervention activity due and completion dates can be useful for managing and driving completion of intervention activities.

Figure 12. MS-Excel Intervention Activity Tracking List

Review follow-up interviewing gaps

Generating a simple list of participants with interview target, earliest, and due dates, as well as days remaining and interview completion can be useful for managing and driving completion of interviews.

Figure 13. MS-Excel Interview Tracking List

REDCap Development and Production Modes

REDCap has a development and a production mode. The development mode allows one to incrementally build and test project components. The production mode is meant for real data collection and project management. It is possible to make some changes after moving the project from the development to the production mode, but once in production changes should be made with extreme care.

REDCap is actively developed

Researchers using REDCap to manage MOST and other types of studies need to be aware of new features and system changes which may impact aspects of your project. These changes are generally enhancements (new features) which don’t have to be adopted in the middle of a project. New REDCap features may require changes to this manual over time.

Enter the New Projects Tab of REDCap to select a project name and type

Figure 14. Project Setup

Longitudinal Project Setup Steps

1. Main Project Settings

• Use surveys in this project
• Use longitudinal data collection with defined events
• Turn on the Scheduling module
• Turn on the Randomization module

2. Create study arms with Define My Events

• Screening
• Assessment
• tuna
• salmon
• marlin
• bass
• trout
• shark
• carp
• halibut

Why did we not having the screening steps as part of the Assessment arm?

The first event in the screening arm, a brief eligibility interview, is common to all potential study participants. There could be additional events in the screening arm for things like results of biological tests and documentation of a status related to eligibility criteria (e.g., ). The goal of the screening arm is to assess various aspects of eligibility criteria, documenting who is eligible and, if not eligible, the reasons why. Only potential participants who are eligible proceed to the main study. Informed consent may be obtained from eligible individuals near the end of the screening arm.

The first event in the assessment arm is a baseline interview. Other events in the assessment arm include one or more follow-up interviews and randomization. The randomization event in the assessment arm is a manual recording of the assigned study condition by staff. This can be checked against the condition assigned by the randomization module, with corrections made if needed.

Each randomly assigned study condition will have a different mix of events, depending on which level of each intervention component is required in the condition. In a full factorial design, one condition may have few or no events related to intervention activities (e.g., a condition in which all components are assigned at an “off” or “absent” level). Another condition in which multiple components are assigned at an “on” or “present” level will have all of the events associated with each active component.

3. Define study events

4. Define ideal dates/times for events to take place

5. Designate data collection instruments to be administered at each study event

6. Go to the Project Setup tab and locate “Main Project Settings”
7. Enable: “Use longitudinal data collection with defined events”?
8. Find “Enable optional modules and customizations”

9. Select “Scheduling Module (longitudinal only)

Screening and baseline interviews

Locator

Randomization to conditions

Fields related to intervention activities

• Activity
• Date
• Duration
• Staff

First follow-up interview

Second and final follow-up interview